A Method of Target Tracking Based on Monocular Vision for Mobile Robot in Unknown Environment

Abstract

In order to solve the problem of target tracking based on monocular vision for mobile robot in unknown environment, a robot simultaneous localization, map building and target tracking method is proposed. This method can realize the simultaneous online estimation of robot, environment features and target states by using the bearings only observations from monocular sensors. In the process of estimation, the monocular vision based Simultaneous localization and mapping (MVSLAM) runs independent of the Object Tracking(OT), as the basis of the OT, MVSLAM provides the state information of the robot platform for the OT, and OT uses the bearing measurements of target and robot state to estimates the state of target. MVSLAM is based on inverse depth parameterization and running under framework of full probability Extended Kalman Filter (EKF), and another EKF is also used for target tracking independently. The simulation experiments show the performance of the design method, and analyze the problem of observability of Bearing-only tracking. To solve the observability problem, a robot motion control method is presented, under the control of this method, the robot will make satellite surround motion around the target. Finally, the feasibility and accuracy of the method are verified by simulation experiments.